
This paper explores how Bayesian Knowledge Tracing (BKT) can be integrated with a pattern-based approach to enhance the development of virtual reality (VR) based serious games and simulations. These technologies allow for the prediction of user progress and the utilization of Artificial Intelligence (AI) methods to tailor difficulty levels based on individual needs. By combining BKT, pattern-based mechanics, and affective feedback, comprehensive data on user interactions, skills, and emotional states can be collected. This data enables the estimation of learners’ knowledge levels and the prediction of their progress.
serious games, Bayesian Knowledge Tracing, evidence centered design, virtual reality, simulations, educational evaluation, design patterns
serious games, Bayesian Knowledge Tracing, evidence centered design, virtual reality, simulations, educational evaluation, design patterns
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